AI spend is up.
Can you prove the return?
In 30 days, we show whether AI is increasing throughput, where it's creating drag, and what leadership should fix first. You get a score, blocker map, and board-ready roadmap.
No prep needed · 20-minute intro call · Results in 30 days
Weighted across 6 dimensions of AI engineering maturity
What leadership already knows — and still cannot answer
Leadership knows
- AI tool spend is up
- Engineers say they are moving faster
- Delivery timelines have not changed
- Hiring targets are flat
Leadership still cannot answer
- Is AI improving throughput?
- Where did the bottlenecks move?
- What is the ROI on current AI spend?
- Can we ship more with the same team?
Before AEMI
- AI usage unclear across teams
- "We feel faster" but no data
- Board questions go unanswered
- Tool spend rises, ROI unknown
After AEMI
- Clear score across every workflow
- Known bottlenecks, ranked by impact
- Prioritized roadmap with next steps
- Board-ready explanation of AI ROI
Where AI creates leverage — and where it quietly creates drag
Your CEO wants to know if AI is increasing throughput. Your CFO wants to know why tool spend is up without a clean ROI story. Your engineering leads know the answer is mixed — some workflows got faster, others got noisier.
No one can say where AI helps
Tools are deployed. Nobody measures whether delivery actually improved.
Bottlenecks moved, not removed
Code gets generated faster. Review, QA, and release absorb the extra load.
Tool rollout without workflow change
AI at the prompt level. Same review process, same release cadence, same governance.
No story for the board
Leadership gets anecdotes. Not a score, not a blocker map, not a plan.
“Developers believed they were 20% faster using AI even when actual performance declined.”
METR Randomized Controlled Trial, 2025
That gap between perception and reality is what AEMI measures.
What AEMI reveals that dashboards miss
What AEMI measures across the delivery system
AEMI looks at the full delivery system — not just who has a coding assistant license.
Most companies only measure coding. AEMI measures the full delivery system.
Workflow fit
Where AI speeds work up and where it creates more cleanup.
Review and QA load
How AI-generated code affects review time, defect rates, and handoffs.
Release infrastructure
Whether CI/CD and release process can absorb faster output.
Knowledge and context
Whether teams can give AI enough context to produce reliable work.
Governance
How policy and approval guardrails affect adoption and risk.
Measurement
Whether leadership can see AI impact in throughput, quality, and cost.
What you get in 30 days
Maturity score
Weighted across workflow fit, controls, adoption, and delivery impact.
Blocker map
Specific bottlenecks slowing AI leverage across the SDLC.
Prioritized roadmap
Ranked by business impact, effort, and time to payoff.
Executive readout
Board-ready narrative for CEO, CFO, or operating partner.
AEMI also establishes the baseline for lagging metrics like cycle time, change failure rate, QA hours, and cost per feature. See a redacted sample engagement pack →
Where most teams are today
8-figure SaaS team: maturity 1.4 → 3.2 in 45 days
129% improvement. From ad hoc experimentation to daily, structured AI-assisted development
- Ad hoc, unmeasured AI usage
- Low trust in AI outputs
- No codebase-specific workflows
- Release prep heavily manual
- 80%+ daily AI usage
- 7 codebase-specific AI workflows
- 20% lower code review cycle time
- 20% faster release prep
What changed for the team
How the assessment works
Discovery
Leadership interviews, workflow inventory, tooling baseline.
You get: workflow inventory and tooling baseline.System review
How AI is used across engineering workflows, controls, and handoffs.
You get: visibility into where AI helps vs adds drag.Analysis
Score maturity, identify blockers, rank fixes by impact.
You get: maturity score, blocker ranking, impact model.Readout
Deliver the score, blocker map, and roadmap.
You get: executive summary and prioritized roadmap.Who this is for
Good fit
- AI tools deployed, need to know if they work
- Leadership wants a clean ROI story, not anecdotes
- Engineering leads know the answer is mixed
- You need a roadmap, not a workshop
Not a fit
- Looking for a one-day AI workshop
- Need prompt training only
- No internal owner for process changes
- Haven't adopted AI tools yet
See if AI is actually paying off
20 minutes with a CTO. We'll tell you if AEMI is right for your team. No pitch deck.